Federated Learning (FL) enables the collaborative training of machine learning models across distributed clients without sharing raw data, offering a promising approach for privacy-preserving artificial intelligence. However, this paradigm remains exposed to a wide range of security and privacy threats, including poisoning, backdoor insertion, inference, and communication-level attacks. To address these challenges, the emerging discipline of Machine Learning Security Operations (MLSecOps) extends DevSecOps principles to the lifecycle of ML models, integrating continuous security testing, monitoring, and resilience verification.
- Load your SSH private key into the SSH agent:
ssh-add private_key- Run the playbook:
ansible-playbook playbooks/site.yml- BENDRAOU Ayoub
- OUCHTA Nazih
- GHOUDANE Salim
- FSAHI Aya